Organizations may be interested in monitoring communications related to items of interest (e.g., topics, products, brands, etc.), and/or may be interested in understanding a nature and context of communications regarding topics of interest both within the organization and communications from public sources of data. Communications within the organization may refer to emails, letters, telephone calls, etc. Public data communications may comprise social media data, community data and any other type of public data. The communications may pertain to a wide range of different topics directed to sales inquiries, customer complaints, product feedback, etc.
It may be beneficial to the organization to understand a content and context of the communications, and monitor communications based on topics of interest to the organization. In many cases, these communications may have to be sorted out manually, organized to understand a quantity and/or quality of the communications, and then be directed to a designated person or authority within the organization. However, manually handling these communications in order to determine the context of communications and an extent/degree of the communications is extremely time-consuming. Given the overwhelming quantity of such messages received by a typical organization (e.g., business, non-profit, or any other entity) it is evident that a manual approach to process these messages can be quite tedious, inefficient, and does not scale very well for many organizations.
Automated processes have been used, but results of such automation tend to be hit or miss since conventional processes are often focused on the simple process of using keyword searching/matching. This approach can be very problematic if the message does not contain the appropriate keyword from a list of pre-programmed keywords, or if the keyword matched in the message pertains to a topic that does not accurately correspond to the true topic of the message. Further, this approach requires a user at the organization to routinely check for the pre-programmed keywords, which proves to be highly time-consuming and inefficient.
Often, traditional approaches of receiving communications related to an organization tend to be slower when compared to communications developing around a topic in social media or other social outlets. However, receiving these communications on a timely basis can be hugely beneficial to the organization in order to appropriately respond and/or perform tasks based on this information. For example, consider an organization that has recently launched a product. It may be beneficial to understand the context and significance of the general chatter around the launched product, and to be notified of the extent, significance and/or the direction (e.g., positive feedback, negative feedback, etc.) of the communications that are taking place in both private and public platforms.
Therefore, there is a need for an improved approach to analyze and process communications related to an organization and timely communicate a content and/or analysis of the communications to the appropriate authority at the organization. Other additional objects, features, and advantages of the invention are described in the detailed description, figures, and claims.